Search (30 results, page 1 of 2)

  • × language_ss:"e"
  • × theme_ss:"Automatisches Indexieren"
  1. Gibb, F.; Smart, G.: Knowledge-based indexing : the view from SIMPR (1991) 0.04
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  2. Thirion, B.; Leroy, J.P.; Baudic, F.; Douyère, M.; Piot, J.; Darmoni, S.J.: SDI selecting, decribing, and indexing : did you mean automatically? (2001) 0.03
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  3. Advances in intelligent retrieval: Proc. of a conference ... Wadham College, Oxford, 16.-17.4.1985 (1986) 0.02
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    Content
    Enthält die Beiträge: ADDIS, T.: Extended relational analysis: a design approach to knowledge-based systems; PARKINSON, D.: Supercomputers and non-numeric processing; McGREGOR, D.R. u. J.R. MALONE: An architectural approach to advances in information retrieval; ALLEN, M.J. u. O.S. HARRISON: Word processing and information retrieval: some practical problems; MURTAGH, F.: Clustering and nearest neighborhood searching; ENSER, P.G.B.: Experimenting with the automatic classification of books; TESKEY, N. u. Z. RAZAK: An analysis of ranking for free text retrieval systems; ZARRI, G.P.: Interactive information retrieval: an artificial intelligence approach to deal with biographical data; HANCOX, P. u. F. SMITH: A case system processor for the PRECIS indexing language; ROUAULT, J.: Linguistic methods in information retrieval systems; ARAGON-RAMIREZ, V. u. C.D. PAICE: Design of a system for the online elucidation of natural language search statements; BROOKS, H.M., P.J. DANIELS u. N.J. BELKIN: Problem descriptions and user models: developing an intelligent interface for document retrieval systems; BLACK, W.J., P. HARGREAVES u. P.B. MAYES: HEADS: a cataloguing advisory system; BELL, D.A.: An architecture for integrating data, knowledge, and information bases
  4. Can, F.: Incremental clustering for dynamic information processing (1993) 0.02
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  5. Siebenkäs, A.; Markscheffel, B.: Conception of a workflow for the semi-automatic construction of a thesaurus for the German printing industry (2015) 0.02
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    Source
    Re:inventing information science in the networked society: Proceedings of the 14th International Symposium on Information Science, Zadar/Croatia, 19th-21st May 2015. Eds.: F. Pehar, C. Schloegl u. C. Wolff
  6. Simões, M. da Graça; Machado, L.M.; Souza, R.R.; Almeida, M.B.; Tavares Lopes, A.: Automatic indexing and ontologies : the consistency of research chronology and authoring in the context of Information Science (2018) 0.02
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    Source
    Challenges and opportunities for knowledge organization in the digital age: proceedings of the Fifteenth International ISKO Conference, 9-11 July 2018, Porto, Portugal / organized by: International Society for Knowledge Organization (ISKO), ISKO Spain and Portugal Chapter, University of Porto - Faculty of Arts and Humanities, Research Centre in Communication, Information and Digital Culture (CIC.digital) - Porto. Eds.: F. Ribeiro u. M.E. Cerveira
  7. Voorhees, E.M.: Implementing agglomerative hierarchic clustering algorithms for use in document retrieval (1986) 0.02
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    Source
    Information processing and management. 22(1986) no.6, S.465-476
  8. Galvez, C.; Moya-Anegón, F. de: ¬An evaluation of conflation accuracy using finite-state transducers (2006) 0.02
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  9. Fauzi, F.; Belkhatir, M.: Multifaceted conceptual image indexing on the world wide web (2013) 0.02
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  10. Gil-Leiva, I.: SISA-automatic indexing system for scientific articles : experiments with location heuristics rules versus TF-IDF rules (2017) 0.02
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    Abstract
    Indexing is contextualized and a brief description is provided of some of the most used automatic indexing systems. We describe SISA, a system which uses location heuristics rules, statistical rules like term frequency (TF) or TF-IDF to obtain automatic or semi-automatic indexing, depending on the user's preference. The aim of this research is to ascertain which rules (location heuristics rules or TF-IDF rules) provide the best indexing terms. SISA is used to obtain the automatic indexing of 200 scientific articles on fruit growing written in Portuguese. It uses, on the one hand, location heuristics rules founded on the value of certain parts of the articles for indexing such as titles, abstracts, keywords, headings, first paragraph, conclusions and references and, on the other, TF-IDF rules. The indexing is then evaluated to ascertain retrieval performance through recall, precision and f-measure. Automatic indexing of the articles with location heuristics rules provided the best results with the evaluation measures.
  11. Hlava, M.M.K.: Automatic indexing : comparing rule-based and statistics-based indexing systems (2005) 0.01
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    Source
    Information outlook. 9(2005) no.8, S.22-23
  12. Li, W.; Wong, K.-F.; Yuan, C.: Toward automatic Chinese temporal information extraction (2001) 0.01
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  13. Tsai, C.-F.; McGarry, K.; Tait, J.: Qualitative evaluation of automatic assignment of keywords to images (2006) 0.01
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  14. Chung, E.-K.; Miksa, S.; Hastings, S.K.: ¬A framework of automatic subject term assignment for text categorization : an indexing conception-based approach (2010) 0.01
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    Abstract
    The purpose of this study is to examine whether the understandings of subject-indexing processes conducted by human indexers have a positive impact on the effectiveness of automatic subject term assignment through text categorization (TC). More specifically, human indexers' subject-indexing approaches, or conceptions, in conjunction with semantic sources were explored in the context of a typical scientific journal article dataset. Based on the premise that subject indexing approaches or conceptions with semantic sources are important for automatic subject term assignment through TC, this study proposed an indexing conception-based framework. For the purpose of this study, two research questions were explored: To what extent are semantic sources effective? To what extent are indexing conceptions effective? The experiments were conducted using a Support Vector Machine implementation in WEKA (I.H. Witten & E. Frank, [2000]). Using F-measure, the experiment results showed that cited works, source title, and title were as effective as the full text while a keyword was found more effective than the full text. In addition, the findings showed that an indexing conception-based framework was more effective than the full text. The content-oriented and the document-oriented indexing approaches especially were found more effective than the full text. Among three indexing conception-based approaches, the content-oriented approach and the document-oriented approach were more effective than the domain-oriented approach. In other words, in the context of a typical scientific journal article dataset, the objective contents and authors' intentions were more desirable for automatic subject term assignment via TC than the possible users' needs. The findings of this study support that incorporation of human indexers' indexing approaches or conception in conjunction with semantic sources has a positive impact on the effectiveness of automatic subject term assignment.
  15. Biebricher, N.; Fuhr, N.; Lustig, G.; Schwantner, M.; Knorz, G.: ¬The automatic indexing system AIR/PHYS : from research to application (1988) 0.01
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    Date
    16. 8.1998 12:51:22
  16. Kutschekmanesch, S.; Lutes, B.; Moelle, K.; Thiel, U.; Tzeras, K.: Automated multilingual indexing : a synthesis of rule-based and thesaurus-based methods (1998) 0.01
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    Source
    Information und Märkte: 50. Deutscher Dokumentartag 1998, Kongreß der Deutschen Gesellschaft für Dokumentation e.V. (DGD), Rheinische Friedrich-Wilhelms-Universität Bonn, 22.-24. September 1998. Hrsg. von Marlies Ockenfeld u. Gerhard J. Mantwill
  17. Stankovic, R. et al.: Indexing of textual databases based on lexical resources : a case study for Serbian (2016) 0.01
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    Date
    1. 2.2016 18:25:22
  18. SIGIR'92 : Proceedings of the 15th Annual International ACM SIGIR Conference on Research and Development in Information Retrieval (1992) 0.01
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    Content
    HARMAN, D.: Relevance feedback revisited; AALBERSBERG, I.J.: Incremental relevance feedback; TAGUE-SUTCLIFFE, J.: Measuring the informativeness of a retrieval process; LEWIS, D.D.: An evaluation of phrasal and clustered representations on a text categorization task; BLOSSEVILLE, M.J., G. HÉBRAIL, M.G. MONTEIL u. N. PÉNOT: Automatic document classification: natural language processing, statistical analysis, and expert system techniques used together; MASAND, B., G. LINOFF u. D. WALTZ: Classifying news stories using memory based reasoning; KEEN, E.M.: Term position ranking: some new test results; CROUCH, C.J. u. B. YANG: Experiments in automatic statistical thesaurus construction; GREFENSTETTE, G.: Use of syntactic context to produce term association lists for text retrieval; ANICK, P.G. u. R.A. FLYNN: Versioning of full-text information retrieval system; BURKOWSKI, F.J.: Retrieval activities in a database consisting of heterogeneous collections; DEERWESTER, S.C., K. WACLENA u. M. LaMAR: A textual object management system; NIE, J.-Y.:Towards a probabilistic modal logic for semantic-based information retrieval; WANG, A.W., S.K.M. WONG u. Y.Y. YAO: An analysis of vector space models based on computational geometry; BARTELL, B.T., G.W. COTTRELL u. R.K. BELEW: Latent semantic indexing is an optimal special case of multidimensional scaling; GLAVITSCH, U. u. P. SCHÄUBLE: A system for retrieving speech documents; MARGULIS, E.L.: N-Poisson document modelling; HESS, M.: An incrementally extensible document retrieval system based on linguistics and logical principles; COOPER, W.S., F.C. GEY u. D.P. DABNEY: Probabilistic retrieval based on staged logistic regression; FUHR, N.: Integration of probabilistic fact and text retrieval; CROFT, B., L.A. SMITH u. H. TURTLE: A loosely-coupled integration of a text retrieval system and an object-oriented database system; DUMAIS, S.T. u. J. NIELSEN: Automating the assignement of submitted manuscripts to reviewers; GOST, M.A. u. M. MASOTTI: Design of an OPAC database to permit different subject searching accesses; ROBERTSON, A.M. u. P. WILLETT: Searching for historical word forms in a database of 17th century English text using spelling correction methods; FAX, E.A., Q.F. CHEN u. L.S. HEATH: A faster algorithm for constructing minimal perfect hash functions; MOFFAT, A. u. J. ZOBEL: Parameterised compression for sparse bitmaps; GRANDI, F., P. TIBERIO u. P. Zezula: Frame-sliced patitioned parallel signature files; ALLEN, B.: Cognitive differences in end user searching of a CD-ROM index; SONNENWALD, D.H.: Developing a theory to guide the process of designing information retrieval systems; CUTTING, D.R., J.O. PEDERSEN, D. KARGER, u. J.W. TUKEY: Scatter/ Gather: a cluster-based approach to browsing large document collections; CHALMERS, M. u. P. CHITSON: Bead: Explorations in information visualization; WILLIAMSON, C. u. B. SHNEIDERMAN: The dynamic HomeFinder: evaluating dynamic queries in a real-estate information exploring system
  19. Tsujii, J.-I.: Automatic acquisition of semantic collocation from corpora (1995) 0.01
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    Date
    31. 7.1996 9:22:19
  20. Riloff, E.: ¬An empirical study of automated dictionary construction for information extraction in three domains (1996) 0.01
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    Date
    6. 3.1997 16:22:15